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Alibaba-backed Moonshot releases Kimi K2 AI rivaling ChatGPT, Claude

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An AI sign at the MWC Shanghai tech show on June 19, 2025.

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BEIJING — The latest Chinese generative artificial intelligence model to take on OpenAI’s ChatGPT is offering coding capabilities — at a lower price.

Alibaba-backed startup Moonshot released on late Friday night its Kimi K2 model: a low-cost, open source large language model — the two factors that underpinned China-based DeepSeek’s industry disruption in January. Open-source technology provides source code access for free, an approach that few U.S. tech giants have taken, other than Meta and Google to some extent.

Coincidentally, OpenAI CEO Sam Altman announced early Saturday that there would be an indefinite delay of its first open-source model yet again due to safety concerns. OpenAI did not immediately respond to a CNBC request for comment on Kimi K2.

Rethinking the AI coding payoff

One of Kimi K2’s strengths is in writing computer code for applications, an area in which businesses see potential to reduce or replace staff with generative AI. OpenAI’s U.S. rival Anthropic focused on coding with its Claude Opus 4 model released in late May.

In its release announcement on social media platforms X and GitHub, Moonshot claimed Kimi K2 surpassed Claude Opus 4 on two benchmarks, and had better overall performance than OpenAI’s coding-focused GPT-4.1 model, based on several industry metrics.

“No doubt [Kimi K2 is] a globally competitive model, and it’s open sourced,” Wei Sun, principal analyst in artificial intelligence at Counterpoint, said in an email Monday.

Cheaper option

“On top of that, it has lower token costs, making it attractive for large-scale or budget-sensitive deployments,” she said.

The new K2 model is available via Kimi’s app and browser interface for free unlike ChatGPT or Claude, which charge monthly subscriptions for their latest AI models.

Kimi is also only charging 15 cents for every 1 million input tokens, and $2.50 per 1 million output tokens, according to its website. Tokens are a way of measuring data for AI model processing.

In contrast, Claude Opus 4 charges 100 times more for input — $15 per million tokens — and 30 times more for output — $75 per million tokens. Meanwhile, for every one million tokens, GPT-4.1 charges $2 for input and $8 for output.

Moonshot AI said on GitHub that developers can use K2 however they wish, with the only requirement that they display “Kimi K2” on the user interface if the commercial product or service has more than 100 million monthly active users, or makes the equivalent of $20 million in monthly revenue.

Hot AI market

Initial reviews of K2 on both English and Chinese social media have largely been positive, although there are some reports of hallucinations, a prevalent issue in generative AI, in which the models make up information.

Still, K2 is “the first model I feel comfortable using in production since Claude 3.5 Sonnet,” Pietro Schirano, founder of startup MagicPath that offers AI tools for design, said in a post on X.

Moonshot has open sourced some of its prior AI models. The company’s chatbot surged in popularity early last year as China’s alternative to ChatGPT, which isn’t officially available in the country. But similar chatbots from ByteDance and Tencent have since crowded the market, while tech giant Baidu has revamped its core search engine with AI tools.

Kimi’s latest AI release comes as investors eye Chinese alternatives to U.S. tech in the global AI competition.

Still, despite the excitement about DeepSeek, the privately-held company has yet to announce a major upgrade to its R1 and V3 model. Meanwhile, Manus AI, a Chinese startup that emerged earlier this year as another DeepSeek-type upstart, has relocated its headquarters to Singapore.

Over in the U.S., OpenAI also has yet to reveal GPT-5.

Work on GPT-5 may be taking up engineering resources, preventing OpenAI from progressing on its open-source model, Counterpoint’s Sun said, adding that it’s challenging to release a powerful open-source model without undermining the competitive advantage of a proprietary model.

Grok 4 competitor

Kimi K2 is not the company’s only recent release. Moonshot launched a Kimi research model last month and claimed it matched Google’s Gemini Deep Research ‘s 26.9 score and beat OpenAI’s version on a benchmark called “Humanity’s Last Exam.”

The Kimi research model even got a mention last week during Elon Musk’s xAI release of Grok 4 — which scored 25.4 on its own on the “Humanity’s Last Exam” benchmark, but attained a 44.4 score when allowed to use a variety of AI tools and web search.

“Kimi-Researcher represents a paradigm shift in agentic AI,” said Winston Ma, adjunct professor at NYU School of Law. He was referring to AI’s capability of simultaneously making several decisions on its own to complete a complex task.

“Instead of merely generating fluent responses, it demonstrates autonomous reasoning at an expert level — the kind of complex cognitive work previously missing from LLMs,” Ma said. He is also author of “The Digital War: How China’s Tech Power Shapes the Future of AI, Blockchain and Cyberspace.”

— CNBC’s Victoria Yeo contributed to this report.

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Treasury Yields Rise as Fed Cut Expectations Shift

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Treasury Yields Rise as Fed Cut Expectations Shift

Fixed-income markets recorded significant re-pricing during the week ending July 25, 2026, as a convergence of strong labor market metrics and surging energy costs drove U.S. Treasury yields higher across all maturities. The benchmark 10-year Treasury yield climbed toward 4.70%, reaching its highest point in several months. Institutional bond investors rapidly adjusted portfolio durations as expectations for near-term interest rate cuts by the Federal Reserve faded in response to inflation concerns.

The upward shift in sovereign yields reflects a broader fundamental reassessment of global monetary policy. Earlier in the quarter, money markets had priced in a series of rate reductions designed to support economic activity. However, with initial jobless claims falling to 187,000 and crude oil breaching $100 per barrel, fixed-income traders are pricing in a ‘higher-for-longer’ interest rate environment. The inversion between short-term Treasury bills and long-term bonds narrowed, indicating a shift toward term premium expansion.

Rising Treasury yields present both challenges and opportunities for institutional wealth managers. While commercial lenders and mortgage origination volumes face headwinds from elevated borrowing costs, fixed-income investors are locking in attractive real yields on high-quality sovereign and investment-grade corporate bonds. Institutional debt issuers, conversely, are recalibrating their capital structures, opting for shorter-term refinancing instruments or private credit facilities to avoid committing to elevated long-term coupon rates.

Navigating the current bond market landscape demands strict duration management and credit selection. Wealth advisors recommend maintaining flexible fixed-income allocations, combining short-duration Treasuries with inflation-protected securities (TIPS) to shield capital against potential energy-driven inflation spikes while earning dependable nominal income.

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Private Credit Expansion Transforms Corporate Loans

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Private Credit Expansion Transforms Corporate Loans

Private credit markets reached a pivotal milestone during the week ending July 25, 2026, as non-bank direct lending consortiums captured a record share of middle-market corporate debt originations. With commercial banks maintaining conservative credit standards and public bond yields remaining elevated, corporate borrowers are increasingly turning to private fund managers for customized capital solutions. This expansion marks a permanent structural shift in enterprise finance, establishing private credit as a primary pillar of institutional corporate liquidity.

The acceleration of private credit deals is driven by speed, deal certainty, and flexible terms. Unlike traditional syndicated bank loans that require lengthy underwriting, credit rating approvals, and public roadshows, private direct lenders can structure tailored financing packages within days. Middle-market firms facing upcoming debt maturities are utilizing private debt facilities to execute recapitalizations, strategic acquisitions, and growth capital deployments without risking execution delay in public markets.

However, financial regulators and central bank supervisors are scrutinizing the sector’s rapid growth. Supervisory agencies are evaluating potential systemic risks associated with non-bank leverage, valuation transparency, and liquidity mismatches during economic downturns. Despite regulatory interest, major pension funds, insurance firms, and sovereign wealth entities continue to expand capital allocations to private credit funds, attracted by reliable floating-rate yields that outperform public fixed-income benchmarks.

As private credit matures into a dominant asset class, corporate chief financial officers must evaluate non-bank lenders alongside traditional banking relationships. Direct lending partnerships provide valuable balance sheet resilience, enabling companies to secure flexible financing terms even during periods of public market turbulence.

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Tokenized Debt Shifts How Corporate Manage Short Term Liquidity

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Tokenized Debt Shifts Corporate Liquidity

The landscape of institutional debt markets is undergoing a profound structural shift on July 21, 2026, as major corporate issuers and commercial banks rapidly accelerate the deployment of tokenized debt instruments. Data published by leading capital market consortiums indicates that primary issuances of digital commercial paper and tokenized corporate bonds have reached record volumes this month. By moving legacy debt origination, underwriting, and secondary distribution onto permissioned distributed ledgers, corporate treasurers are unlocking unprecedented operational flexibility and instantaneous cross-border liquidity.

The adoption of tokenized debt is fundamentally altering how enterprise balance sheets manage short-term liquidity needs. Traditional corporate bond settlement cycles historically required multi-day clearing processes involving numerous intermediaries, custodial entities, and clearinghouses. Through programmable smart contracts on distributed ledgers, issuers can now execute atomic settlement—enabling continuous, 24/7 access to institutional capital pools. This instantaneous clearing mechanism drastically reduces counterparty risk, eliminates costly settlement friction, and allows treasury teams to dynamically optimize working capital in real time.

A major catalyst driving this institutional migration is the establishment of comprehensive digital asset regulatory frameworks across major financial hubs. Clear legal guidelines regarding ledger-based securities ownership have provided institutional compliance officers with the regulatory confidence necessary to transition multi-billion-dollar liquidity facilities onto digital platforms. Furthermore, the integration of automated regulatory reporting directly into token smart contracts simplifies ongoing compliance audits, ensuring that secondary market trades automatically enforce investor accreditation limits and tax withholding requirements.

For chief financial officers and institutional portfolio managers, tokenized debt represents a fundamental evolution in fixed-income strategy. Companies that embrace ledger-based debt structures gain direct access to a broader, global base of digital-native institutional investors while substantially reducing borrowing overhead. As ledger interoperability continues to improve across global exchanges, tokenized debt is poised to become the standard infrastructure for global corporate finance.

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